Efficiency and Cost Saving of 7 Day Per Week Exercise Testing Utilizing All Electrocardiography Technologists
Bibliographic record
Abstract
BACKGROUND: In most centers, exercise testing (ET) is performed by one or two trained technologists during the weekdays (0800 hours-1600 hours), leaving a void during evenings and weekends. This leads to unnecessary increased costs due to delays in management of patients. Electrocardiography technologists (ECGT) are often available for extended hours. This project was undertaken to improve the efficiency of the ET laboratory by using ECGT to perform ET during these extended hours. METHODS: Clinical utility and cost saving of a 7 day per week ET for management of patients with suspected and/or known coronary artery disease utilizing ECGT was assessed after adequate training. Of 4099 patients undergoing ET between January 1995 and December 1997, 810 tests performed by ECGT were reviewed retrospectively. RESULTS: Of the 810 patients (age mean 58.4 +/- 0.44 yrs; range 16-88; males: 508, females: 302), 806 (99.5%) underwent the Bruce protocol. The indications were: diagnostic, 61.3%, predischarge acute myocardial infarction (AMI), 17.7%, evaluation of angina, 19.6%, other, 1.4%. Only 8 (0.1%) patients had complications (prolonged chest pain, 6; nonsustained ventricular tachycardia, 2) with no AMIs or deaths. This strategy resulted in a savings of 158 bed days (Can189,600 dollars) on inpatients and 15 bed days (Can18,000 dollars) on those presenting to the emergency department. CONCLUSIONS: This study demonstrates the feasibility and safety of utilizing ECGT for ET thus extending the hours of service. This resulted in efficient patient management, with a considerable cost-saving to the hospital.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".